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检索条件"任意字段=7th International Symposium on Parallel and Distributed Computing"

共 1408 条记录，以下是61-70 订阅

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Effect of parallel TCP stream equalizer on real long fat-pipe network

Effect of parallel TCP stream equalizer on real long fat-pip...

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7th IEEE international symposium on Networking computing and Applications, NCA 2008

作者： Sugawara, Yutaka Tezuka, Hiroshi Inaba, Mary Hiraki, Kei Yoshino, Takeshi University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan Google Japan Inc.

ISBN: (纸本)9780769531922

With the rapid progress of high-performance cluster applications, data transfer between clusters in distant locations becomes more important. But, it is difficult to transfer data using parallel TCP streams on long distance high bandwidth network. In this paper, we microscopically observe parallel TCP streams on 10Gbps network using our network analyzer, propose, implement, and evaluate "Stream Equalizer" which relaxes self-congestion and balances throughput among streams. We evaluate it using a real wide-area network over the Pacific Ocean. the network analyzer and the Stream Equalizer are implemented on FPGA-based programmable high-speed network testbed TGNLE-1. © 2008 IEEE.

关键词： Equalizers

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Effect of optimal allocation of multiple DG and D-STATCOM in radial distribution system for minimising losses and thD 7

Effect of optimal allocation of multiple DG and D-STATCOM in...

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7th international symposium on Embedded computing and System Design (ISED)

作者： Gupta, Atma Ram NIT Kurukshetra Elect Engn Dept Kurukshetra 136119 Haryana India

ISBN: (纸本)9781538630327

the expansion of power system has led to the increase of distributed Generation (DG) to fulfil the increase in the load demand. the DG opted has led to the increase in the losses and voltage imbalance due to improper allocation. Rapid increase in nonlinear loads in our daily life has introduced the power quality problems in the power system in terms of harmonics. In this paper, the optimal placement of multiple DG and Distribution Static Compensator (D-STATCOM) in a radial distribution system is carried out which results in the reduction of line losses as well as Total Harmonic Distortion (thD). the optimal location of DG and D-STATCOM is determined by stability index. the optimal size of DG and D-STATCOM is determined using variation technique by increasing the size in steps. the load flow analysis and harmonic flow analysis is carried out on IEEE 34 bus system having the harmonic sources injected as current sources.

关键词： distributed generation D-STATCOM load flow harmonic load flow sensitivity analysis radial distribution system

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Adaptive performance modeling on hierarchical grid computing environments 07

Adaptive performance modeling on hierarchical grid computing...

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7th IEEE international symposium on Cluster computing and the Grid

作者： Nasri, Wahid Steffenel, Luiz Angelo Trystram, Denis ESSTT Dept Informat Tunis Tunisia Univ Nancy 2 Nancy France INPG LaboID IMAG Grenoble France

ISBN: (纸本)9780769528335

In the past, efficient parallel algorithms have always been developed specifically for the successive generations of parallel systems (vector machines, shared-memory machines, distributed-memory machines, etc.). Today, due to many reasons, such as the inherent heterogeneity, the diversify, and the continuous evolution of the existing parallel execution supports, it is very, hard to solve efficiently a target problem by using a single algorithm or to write portable programs that perform well on an), computational supports. Toward this goal, we propose a generic framework based on communication models and adaptive approaches in order to adaptively model performances on grid computing environments. We apply, this methodology on collective communication operations and show, by achieving experiments on a real platform, that the framework provides significant performances while determining the best combination model-algorithm depending on the problem and architecture parameters.

关键词： cluster computing performance modeling adaptive techniques polymodels of communications collective communication operations

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Vertex-centric parallel Algorithms for Identifying Key Vertices in Large-scale Graphs 17

Vertex-centric Parallel Algorithms for Identifying Key Verti...

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2015 IEEE 17th international Conference on High Performance computing and Communications (HPCC)

作者： Li, Bo Gao, Zhuangliang Niu, Jianwei Lv, YanFei Zhang, Hong Beihang Univ Sch Comp Sci & Engn Beijing Peoples R China CNCERT CC Beijing Peoples R China

ISBN: (纸本)9781479989379

Betweenness centrality is a metric to measure the relative importance of vertices within a graph. the computation of betweenness centrality is based on shortest paths which requires O(n+m) space and O(mn) and O(nm+n(2) log n) time on unweighted and weighted graphs, respectively. It is time-consuming to deal with large-scale graphs, which motivates us resort to distributed computing and parallel algorithms. In this paper, we design a vertex-based parallel algorithm following the shortest path approach (SPBC). Moreover, we propose a distributed algorithm based on message propagation (MPBC) to quantify the importance of vertices. MPBC takes into account the real situation of information diffusion in social networks. We implement our algorithms on Graphlab and evaluate them through comprehensive experiments. the results show that both SPBC and MPBC scale well with the increasing number of machines. SPBC on 2 machines outperforms the classical centralized algorithm by 1.59 times in terms of running time. MPBC can handle graph with ten millions of vertices and edges within an acceptable time where classical algorithms become infeasible.

关键词： key vertices parallel algorithm SPBC MPBC

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Privacy Preserving Fuzzy Co-clustering with distributed Cooccurrence Matrices 7

Privacy Preserving Fuzzy Co-clustering with Distributed Cooc...

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Joint 7th international Conference on Soft computing and Intelligent Systems (SCIS) and 15th international symposium on Advanced Intelligent Systems (ISIS)

作者： Tanaka, Daiji Oda, Toshiya Honda, Katsuhiro Notsu, Akira Osaka Prefecture Univ Grad Sch Engn Sakai Osaka 5998531 Japan

ISBN: (纸本)9781479959556

Privacy preserving data mining is a promising topic for utilizing various personal information without fear of information leaks. Fuzzy co-clustering is a fundamental technique for summarizing mutual cooccurrence information among objects and items, and has been demonstrated to be useful in such applications as document analysis and collaborative filtering. In this paper, a secure framework for privacy preserving fuzzy co-clustering is proposed for handling both vertically and horizontally distributed cooccurrence matrices. Personal observation stored in each site is summarized into co-cluster structures with an encryption operation. the advantage of utilizing distributed cooccurrence matrices is demonstrated in several numerical experiments.

关键词： data mining data privacy matrix algebra pattern clustering collaborative filtering distributed cooccurrence matrices document analysis encryption operation personal information privacy preserving data mining privacy preserving fuzzy coclustering Clustering algorithms Collaboration Data privacy distributed databases Encryption Privacy Vectors Data privacy Data Security collaborative filtering distributed databases Privacy cryptography Clustering algorithms matrix algebra data mining Cluster Analysis Content analysis

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Implementation of distributed application using RMI Java threads

Implementation of distributed application using RMI Java thr...

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7th IEEE international symposium on Signal Processing and Information Technology

作者： Keshk, Arabi E. Menoufia Univ Fac Comp & Informat Menoufia Egypt

ISBN: (纸本)9781424418343

In this paper, we suggest a mechanism for implementing a distributed application using RMI based on JAVA threads. the application is parallel matrices multiplication depending on distributed the products of rows and columns on different machines. One server and three clients are run to find the product of matrix multiplication. the server distributes the determine blocks of rows and columns on the registered clients. the clients return their product blocks to a server, which calculate the final product of matrix multiplication. Applications of this type will allow loaded servers to transfer part of the load to clients to exploit the computing power available at client side. the time Of matrix multiplication with size of 256 x 256 is reduced by 52.5% by using 3-client and this time can be decreased more in the case of increasing the number of clients.

关键词： computing power

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InDiGO: An Infrastructure for Optimization of distributed Algorithms

InDiGO: An Infrastructure for Optimization of Distributed Al...

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7th international symposium on parallel and distributed computing

作者： Kolesnikov, Valeriy Singh, Gurdip Kansas State Univ Manhattan KS 66506 USA

ISBN: (纸本)9780769534725

the developers of distributed algorithms are faced with two opposing forces. One is to design generic algorithms that are reusable in a large number of applications. Efficiency considerations, on the other hand, force the algorithms to be Customized to specific operational contexts. this problem is often attacked by simply re-implementing all or large portions of an algorithm. this paper proposes InDiGO, ail infrastructure which allows design of generic hut customizable algorithms and provides tools to customize such algorithms for specific applications. InDiGO provides the following capabilities: (a) Tools to generate intermediate representations of an application which can be leveraged for analysis, (b) Mechanisms to allow developers to design customizable algorithms by exposing design knowledge in terms of configurable options, and (c) Ail optimization engine to analyze an application to derive the information necessary optimize the algorithms. We perform three types of optimizations: static, dynamic and physical topology-based optimization. We present experimental results to demonstrate the advantages of our infrastructure.

关键词： Computer software reusability

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Privacy Preserving Extraction of Fuzzy Rules from distributed Data with Different Attributes 7

Privacy Preserving Extraction of Fuzzy Rules from Distribute...

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Joint 7th international Conference on Soft computing and Intelligent Systems (SCIS) and 15th international symposium on Advanced Intelligent Systems (ISIS)

作者： Jiang, Jinsai Umano, Motohide Osaka Prefecture Univ Grad Sch Sci Dept Math & Informat Sci Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan

ISBN: (纸本)9781479959556

Data mining has emerged as a significant technology for discovering knowledge in vast quantities of data. It is, however, accompanied by the danger that private information will be revealed in the processing of data mining. Hence, privacy-preserving data mining has received a growing amount of attention in recent years. We have proposed a method to extract global fuzzy rules from distributed data with the same attributes in a privacy-preserving manner. this method transfers only values necessary for the extraction process without collecting any data at one place and can obtain the global fuzzy rules at all places. In this paper, we propose a method to extract global fuzzy rules in a privacy-preserving manner from distributed data with different attributes based on the method for distributed data with the same attributes. We illustrate a result for experiments using Iris data by R.A. Fisher.

关键词： data mining data privacy fuzzy set theory Iris data distributed data knowledge discovery privacy preserving fuzzy rule extraction privacy-preserving data mining Data privacy distributed databases Educational institutions Fuzzy sets Iris Servers

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Overhead analysis of Grid workflow applications 06

Overhead analysis of Grid workflow applications

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7th IEEE/ACM international Conference on Grid computing

作者： Nerieri, Francesco Prodan, Radu Fahringer, thomas Truong, Hong-Linh Univ Innsbruck Inst Comp Sci Tech Str 21A A-6020 Innsbruck Austria

ISBN: (纸本)9781424403431

In this paper we propose a systematic approach to performance analysis of workflow applications on the Grid. We introduce an ideal model for the workflow execution time and explain the difference to the real measured times based on a hierarchy of performance overheads for Grid computing. We describe how to systematically measure and compute the overheads from individual activities to entire workflow applications. We adjusted well-known parallel processing metrics to the scope of Grid computing, comprising speedup and efficiency. We have implemented and largely automatised our analysis approach in the context of the ASKALON Grid application development and computing environment. We present experimental results that show detailed overhead analysis of two real-world workflow applications executed in a national Grid environment.

关键词： Grid computing Performance analysis Pervasive computing Application software parallel processing Computer applications distributed computing Optimizing compilers Performance loss Middleware

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Palantir: Reseizing Network Proximity in Large-scale distributed computing Frameworks Using SDN 7

Palantir: Reseizing Network Proximity in Large-scale Distrib...

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7th IEEE international Conference on Cloud computing (CLOUD)

作者： Yu, Ze Li, Min Yang, Xin Li, Xiaolin Univ Florida Dept Elect & Comp Engn Gainesville FL 32610 USA

ISBN: (纸本)9781479950638

parallel/distributed computing frameworks, such as MapReduce and Dryad, have been widely adopted to analyze massive data. Traditionally, these frameworks depend on manual configuration to acquire network proximity information to optimize the data placement and task scheduling. However, this approach is cumbersome, inflexible or even infeasible in large-scale deployments, for example, across multiple datacenters. In this paper, we address this problem by utilizing the Software-Defined Networking (SDN) capability. We build Palantir, an SDN service specific for parallel/distributed computing frameworks to abstract the proximity information out of the network. Palantir frees the framework developers/administrators from having to manually configure the network. In addition, Palantir is flexible because it allows different frameworks to define the proximity according to the framework-specific metrics. We design and implement a datacenter-aware MapReduce to demonstrate Palantir's usefullness. Our evaluation shows that, based on Palantir, datacenter-aware MapReduce achieves siginficant performance improvement.

关键词： MapReduce

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